code: def test_instantiation():
      """Tests instantiation."""
      model = LagBasedEstimator(
          coverage=0.95,
          freq="D",
          lag_unit="day",
          lags=[1, 2, 3],
          agg_func="weighted_average",
          agg_func_params={"weights": [3, 2, 1]},
          uncertainty_dict={
              "uncertainty_method": "simple_conditional_residuals",
              "conditional_cols": ["dow_hr"],
              "value_col": "y",
          },
          past_df=pd.DataFrame({}),
          series_na_fill_func=lambda s: s.bfill(),
      )
      assert model.coverage == 0.95
      assert model.freq == "D"
      assert model.lag_unit == "day"
      assert model.lags == [1, 2, 3]
      assert model.agg_func == "weighted_average"
      assert model.agg_func_params == {"weights": [3, 2, 1]}
      assert model.uncertainty_dict == {
          "uncertainty_method": "simple_conditional_residuals",
          "conditional_cols": ["dow_hr"],
          "value_col": "y",
      }
      assert model.past_df.equals(pd.DataFrame({}))
      assert model.df is None
      assert model.uncertainty_model is None
      assert model.max_lag_order is None
      assert model.min_lag_order is None
      assert model.train_start is None
      assert model.train_end is None
  
imports: from datetime import timedelta
  import numpy
  import pandas
  import pytest
  from dateutil.relativedelta import relativedelta
  from testfixtures import LogCapture
  from greykite.common.constants import ERR_STD_COL
  from greykite.common.constants import LOGGER_NAME
  from greykite.common.constants import PREDICTED_COL
  from greykite.common.constants import PREDICTED_LOWER_COL
  from greykite.common.constants import PREDICTED_UPPER_COL
  from greykite.sklearn.estimator.lag_based_estimator import LagBasedEstimator
label_desc: Use image node_id 5 for calling a global function with example usage: test_instantiation() without return types